Sequential and session-based recommendation problems have received substantial attention in academic research in the past few years. While numerous algorithmic approaches are proposed every year for the underlying next-item prediction problem, it turns out that the progress that we make may in fact be rather limited due to widespread methodological issues. Furthermore, the research community continues to focus strongly on prediction accuracy, which is only one of several components of the success of a recommender system in practice. In this talk, we critically review the developments in the literature and provide a subjective selection of important areas which are currently not yet in the focus of the research community.